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iScale: Studying Long-Term Experiences through Memory

  • Evangelos Karapanos
Part of the Studies in Computational Intelligence book series (SCI, volume 436)

Abstract

This chapter presents iScale, a survey tool for the retrospective elicitation of longitudinal user experience data. iScale aims to minimize retrospection bias and employs graphing to impose a process during the reconstruction of one’s experiences. Two versions, the constructive and the value-account iScale, were motivated by two distinct theories on howpeople reconstruct emotional experiences from memory. These two versions were tested in two separate studies. Study 1 aimed at providing qualitative insight into the use of iScale and compared its performance to that of free-hand graphing. Study 2 compared the two versions of iScale to free recall, a control condition that does not impose structure on the reconstruction process. Overall, iScale resulted in an increase in the amount, the richness, and the test-retest consistency of recalled information as compared to free recall. These results provide support for the viability of retrospective techniques as a cost-effective alternative to longitudinal studies.

Keywords

Free Recall Episodic Memory Temporal Information Semantic Memory Experience Report 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  1. 1.Technologies InstituteMadeira InteractiveFunchalPortugal

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